Determining Actual Response Time in P-FRP Using Idle-Period Game Board

2011 ◽  
Author(s):  
Chaitanya Belwal ◽  
Albert M. K. Cheng
Keyword(s):  
Response Time ◽  
Idle Period ◽  
Actual Response ◽  
Game Board

Diffusion and economic growth fuzzy intelligent system based on DSGE model

2020 ◽  
pp. 1-9
Author(s):  
Shuqiang Liu ◽  
Dawei Zhao
Keyword(s):  
Economic Growth ◽  
Response Time ◽  
Intelligent System ◽  
Uncertain Data ◽  
Approximate Reasoning ◽  
Uncertain Information ◽  
Dsge Model ◽  
Actual Response ◽  
Evaluation Information ◽  
Rule Evaluation

In general, there are a lot of uncertainties in uncertain information, natural language, and human knowledge. The conclusion can be better deduced by using an approximate reasoning method, while a fuzzy intelligent system can deal with uncertain data and rule evaluation information systems. In order to better explore diffusion and economic growth, this paper constructs a fuzzy intelligent system based on the DSGE model and uses this system to analyze diffusion and economic growth. In order to verify the feasibility of this system, we test the response time and accuracy of the system. In addition, we also use the system to simulate diffusion and economic growth. The results show that with the increase of the task amount, the gap between the actual response time and the expected response time of the fuzzy intelligent system based on the DSGE model increases. When the task quantity is 20, the expected response time is 2.31 and the actual response time is 2.24. When the task quantity is 40, the expected response time is 2.5 and the actual response time is 2.36. The larger the task quantity is, the faster the response time of a fuzzy intelligent system based on the DSEG model is. Therefore, the fuzzy intelligent system based on the DSEG model has good performance and can analyze diffusion and economic growth well.

scholarly journals A systematic review of ePCR systems on reducing the response time of prehospital medical care

F1000Research ◽  
2021 ◽  
Vol 10 ◽  
pp. 1209
Author(s):  
ALI JASBI ◽  
Saravanan Muthaiyah ◽  
Thein Oak Kyaw Zaw
Keyword(s):  
Systematic Review ◽  
Response Time ◽  
Medical Care ◽  
Prehospital Care ◽  
Considerable Proportion ◽  
Healthcare Organisation ◽  
Care Services ◽  
Prehospital Medical Care ◽  
Actual Response ◽  
The Impact

Background Poor communication at the time of patient handover is recognized as a root cause of a considerable proportion of preventable deaths. Despite several advantages, the Patient Care Report (PCR) implementation may include insufficient details for demonstrating the functional status of the patients during the actual response which can further prolong the response time. Healthcare entities have been emphasizing the need to implement e-PCR systems. This systematic review aimed to examine the impact of e-PCR systems on reducing response time of prehospital care. Methods Literature search was carried out using the relevant search terms and keywords with inclusion and exclusion criteria. N=6 researchers that focused on the impact of e-PCR systems on reducing response time of prehospital medical care were included within this review. Results The findings indicated that ePCR implementation led to prominent improvements in the quality of the care services provided by the healthcare organisation. Additionally, ePCR reduces the response rate by data standardization. Conclusion The implementation of e-PCR systems ensures the availability of records and automates reporting on given quality metrics. Moreover, the implementation of e-PCR systems also improved response time and increased the out of hospital rates of survival. However, fear of increasing the ambulance run time, compromise on the availability of ambulance, and challenges in integration with the existing information systems implemented within the hospitals, were some of the most common challenging situations associated with implementing e-PCR systems.

Temporal Prediction Errors Affect Short-Term Memory Scanning Response Time

2016 ◽  
Vol 63 (6) ◽  
pp. 333-342
Author(s):  
Roberto Limongi ◽  
Angélica M. Silva
Keyword(s):  
Response Time ◽  
Short Term Memory ◽  
Estimation Error ◽  
Predictive Coding ◽  
Time Estimation ◽  
Prediction Errors ◽  
Memory Scanning ◽  
Short Term ◽  
Term Memory ◽  
Temporal Prediction

Abstract. The Sternberg short-term memory scanning task has been used to unveil cognitive operations involved in time perception. Participants produce time intervals during the task, and the researcher explores how task performance affects interval production – where time estimation error is the dependent variable of interest. The perspective of predictive behavior regards time estimation error as a temporal prediction error (PE), an independent variable that controls cognition, behavior, and learning. Based on this perspective, we investigated whether temporal PEs affect short-term memory scanning. Participants performed temporal predictions while they maintained information in memory. Model inference revealed that PEs affected memory scanning response time independently of the memory-set size effect. We discuss the results within the context of formal and mechanistic models of short-term memory scanning and predictive coding, a Bayes-based theory of brain function. We state the hypothesis that our finding could be associated with weak frontostriatal connections and weak striatal activity.

A Response-Time Investigation of Vehicle Stereotypes

2000 ◽  
Author(s):  
Michael Anthony ◽  
Robert W. Fuhrman
Keyword(s):  
Response Time

A Response Time Model on the Role of Spectral and Duration Cues in Vowel Perception

2014 ◽  
Author(s):  
Gabriel Tillman ◽  
Don van Ravenzwaaij ◽  
Scott Brown ◽  
Titia Benders
Keyword(s):  
Response Time ◽  
Time Model ◽  
Vowel Perception ◽  
Response Time Model
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